Model for glutamate racemase inhibitors and glutamate racemase antibacterial agents

ABSTRACT

The increase in antibacterial resistance has created the demand for new antibiotics. The present invention relates to a more potent antibiotic that targets the enzyme glutamate racemase from known glutamate racemase inhibitors. Glutamate racemase catalyses the interconversion of L-glutamate to D-glutamate, making D-glutamate available, which is required for bacterial peptidoglycan biosynthesis. Knockout mutations have shown glutamate racemase to be necessary for bacterial cell survival and, before the present invention, no antibiotic on the market targeted this enzyme. The present invention relates to new, ligand based glutamate racemase inhibitors, developed using software to extract a pharmacophore model from a group of known glutamate racemase inhibitors. Forty-seven (47) known inhibitors were collected from the literature and several pharmacophore models were extracted therefrom. The functional groups common to all the known inhibitors were included in a pharmacophore model that described the requirements for glutamate racemase inhibition with 82% accuracy. Of these models, one was found to describe the requirements for glutamate racemase inhibition with 82% accuracy. The model was used to search databases of commercially available chemical compounds and 2-(2-(1H-indol-3-yl)ethylamino)-4-oxo-4-p-tolylbutanoic acid and 2-(2-(1H-indol-3-yl)ethylamino)-4-(4-fluorophenyl)-4-oxobutanoic acid were identified as showing antibacterial activity. These compounds were assayed against  S. pneumoniae  and were shown to have antibacterial activity against the non-virulent strain R6 and against a multidrug resistant strain.

RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application No.61/105,662, filed on Oct. 15, 2008; U.S. Provisional Application No.61/117,017, filed on Nov. 21, 2008, and U.S. Provisional Application No.61/252,135 filed Oct. 15, 2009, the entire disclosures of which areherein incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to drug discovery and development. Morespecifically, the present invention relates to the development ofglutamate racemase inhibitors as a class of antibiotics with enhancedpharmacokinetic properties. The invention also relates to chemicalcompounds with antibacterial activity against Streptococcus pneumoniae(S. pneumoniae) and a pharmacophore model that can be used to identifyantibacterial drugs with good pharmacokinetic properties. The identifiedantibacterial compounds are inhibitors of the enzyme glutamate racemase,which is a new antibacterial target that none of the current antibioticsin the market target. This represents a new class of antibiotics that,because it has not been used before, has less resistance potential. Thepharmacophore model was designed to identify compounds with less chargedgroups in order to improve their absorption, pharmacokinetic propertiesand antibacterial effectiveness.

BACKGROUND OF THE INVENTION

Antibiotic resistance is a growing problem in the world today.Antibiotic resistant strains of pathogenic bacteria emerge every day andrepresent a significant health care challenge According to Science, in1980 around 1% to 5% of S. aureus was methicillin resistant and today60% to 70% of S. aureus strains found in hospitals are methicillinresistant. This alarming increase in bacterial resistance to antibioticshas motivated an active search for novel viable targets for antibioticdrug design.

Publication Nos. US 2002/0052694 and 2002/0077754 discloses aspecialized apparatus and methods for identifying, representing, andproductively using high activity regions of chemical structure space. Atleast two representations of chemical structure space provide valuableinformation. A first representation has many dimensions representingmembers of a pharmacophore basis set and one or more additionaldimensions representing defined chemical activity (e.g., pharmacologicalactivity). A second representation has many fewer dimensions, each ofwhich represents a principle component obtained by transforming thefirst representation via principal component analysis used onpharmacophore fingerprint/activity data for a collection of compounds.When the collection of compounds has the defined chemical activity, thatactivity will be reflected as a “high activity” region of chemical spacein the second representation.

Publication No. 2005/0009093 discloses a method for generating a focusedcompound library containing an enriched amount of ligand compounds beingcapable of binding to a predetermined receptor.

Publication No. US 2005/0049794 discloses a processes for producing anoptimized pharmacophore for a target protein. The invention also relatesto processes for identifying compounds having an affinity to a targetprotein. The invention also relates to processes for designing a ligandfor a target protein using the optimized pharmacophore of the presentinvention. The invention also provides a computer for use in designing aligand for a target protein using the optimized pharmacophore of thepresent invention.

Publication No. 2005/0053978 discloses methods and systems forgenerating pharmacophore models characterized both by molecular featuresthat are present in the model and features that are defined as absent.Thus, models can be developed that take into account features such assteric bulk that inhibit activity for a specified target as well asfeatures such as functional groups that promote activity. Features thatinhibit activity can be identified by comparing known active moleculeswith known inactive molecules. Features that are present in the inactivemolecules but absent in the active molecules can be defined in apharmacophore model.

Publication No. 2005/0177318 discloses pharmacophores in moleculesidentified by generating a set of conformations for a respectivemolecule. A respective conformation includes a series of features thatare present or absent in the conformation, wherein a respective featureincludes at least two molecular elements and at least one distancebetween the molecular elements. The features for a set of conformationsfor a given molecule are repeatedly compared to a model of featureimportance of remaining molecules, to identify an inferred conformationof a given molecule, until the model of feature importance for themolecules converges.

Publication No. US 2006/0206269 discloses a set of molecules, themembers of which have the same type of biological activity, representedas one-dimensional strings of atoms. The one-dimensional strings of allmembers of the set are aligned, in order to obtain a multiple alignmentprofile of a consensus active compound. The one-dimensional multiplealignment profile is used in deriving a one-dimensional QSAR model toidentify other compounds likely to have the same biological activity,and also may be used to derive a three-dimensional multiple alignmentprofile of the molecules in the set.

Publication No. US 2007/0156343 discloses a stochastic algorithm forpredicting the drug-likeness of molecules. It is based on optimizationof ranges for a set of descriptors. Lipinski's “rule-of-5”, which takesinto account molecular weight, log P, and the number of hydrogen bonddonor and acceptor groups for determining bioavailability, waspreviously unable to distinguish between drugs and non-drugs with itsoriginal set of ranges. The invention demonstrates the predictive powerof the stochastic approach to differentiate between drugs and non-drugsusing only the same four descriptors of Lipinski, but modifying theirranges. However, there are better sets of 4 descriptors to differentiatebetween drugs and non-drugs, as many other sets of descriptors wereobtained by the stochastic algorithm with more predictive power todifferentiate between databases (drugs and non-drugs). A set ofoptimized ranges constitutes a “filter”. In addition to the “best”filter, additional filters (composed of different sets of descriptors)are used that allow a new definition of “drug-like” character bycombining them into a “drug like index” or DLI. In addition to producinga DLI (drug-like index), which permits discrimination betweenpopulations of drug-like and non-drug-like molecules, the presentinvention may be extended to be combined with other known drug screeningor optimizing methods, including but not limited to, high-throughputscreening, combinatorial chemistry, scaffold prioritization and docking.

Publication No. US 2007/0198195 discloses a computational method ofdetermining a set of proposed pharmacophore features describinginteractions between a known biological target and known trainingligands that show activity towards the biological target.

The identification of potentially novel drugs and molecular targets canassist in preventing antibiotic resistance. Bacterial peptidoglycanbiosynthesis is a well validated and a very attractive target for thedesign and discovery of new antibacterial agents since it is unique tobacteria cells (does not occur in humans) and are unexploited steps inthe pathway. Currently, several bactericidal antibiotics available onthe market target the bacterial peptidoglycan biosynthesis pathway,e.g., vancomycin. However, these agents are highly susceptible toresistance.

A new drug target in the peptidoglycan biosynthetic pathway is glutamateracemase (glu racemase), an enzyme which catalyses the conversion ofL-glutamate to D-glutamate providing D-glutamate for peptidoglycanbiosynthesis. Knock-out mutations have shown the glutamate racemase geneto be essential in Escherichia coli (E. coli) and S. pneumoniae.Recently, a group of glutamate racemase inhibitors were developed¹through chemical synthesis but enthusiasm for these agents waned as theypossessed a narrow spectrum of antibacterial activity against only S.pneumoniae. The apparent poor antibacterial activity of these compoundswas due in part to poor membrane permeability. ¹ de Dios A, Prieto L,Martin J A, et al. 4-substituted D-glutamic acid analogues: The firstpotent inhibitors of glutamate racemase (MurI) enzyme with antibacterialactivity. J Med. Chem. 2002; 45:4559-4570

Therefore, a drawback of known glutamate racemase inhibitors is theirpoor lipophilic nature. It was hypothesized that the charged groups inthe D-glu-analogue inhibitors² make them poorly lipophilic and unable topermeate through biological membranes. The minimum inhibitoryconcentration (MIC) from whole-cell assays of some of these inhibitorsdid not correlate with their IC₅₀ values from the in vitro enzyme assaysfurther supporting this hypothesis. In addition, the poor lipophilicnature of these inhibitors makes them poor drug candidates as they willshow poor gut permeability and poor absorption from the intestine. ² Id.

Accordingly, there remains a need for glutamate racemase inhibitors withenhanced lipophilic properties. Eliminating some or all of the chargedgroups enhances the lipophilic nature of these inhibitors and, as aconsequence, enhances their membrane permeability properties which inturn enhances not only their antibacterial spectrum but theirpharmacokinetic profile as well. However, those charged groups may beessential for binding and inhibition of the enzyme. The presentinvention is directed to a method of enhancing the pharmacokineticprofile of the charged poorly lipophilic glu racemase inhibitors whilepreserving their antibacterial activity using a ligand-based drug designapproach.

SUMMARY OF THE INVENTION

One of the unexploited steps in bacterial peptidoglycan biosynthesis isthe step catalyzed by the enzyme glutamate racemase. This enzymecatalyses the conversion of L-glutamate to D-glutamate which is anecessary component in the formation of bacterial peptidoglycan.Knockout mutations in S. pneumoniae have shown glutamate racemase to beessential for the viability of this bacterium. Thus, glutamate racemaseinhibitors represent a new class of antibiotics with less resistancepotential.

The present invention relates to pharmacophore model ADNRR2584, acomputational model that can be used to identify new potent glutamateracemase inhibitors with antibacterial activity and enhanced absorptionproperties, including membrane permeability, through virtual screeningof databases of commercially available chemical compounds. The model ofthe present invention saves time and greatly reduces the expenses in thedrug development process because it can predict the activity ofcommercially available compounds precluding the need for chemicalsynthesis.

It is an object of the present invention to inhibit bacterial growth.

It is another object of the present invention to identify newantibacterial agents with less resistance potential and with enhancedpharmacokinetic properties.

It is another object of the present invention to speed up the process ofantibacterial discovery and reduce the associated cost.

It is another object of the present invention to provide a model thatassigns a predicted activity to the compounds it identifies.

It is a further object of the present invention to provide apharmacophore model for glutamate racemase inhibitors that willfacilitate the identification of new glutamate racemase inhibitors withantibacterial activities.

It is a further object of the present invention to provide apharmacophore model that can be used to screen a large number ofcompounds in silico to identify new antibacterial agents and predicttheir activities.

It is a further object of the present invention to provide apharmacophore model with no more than one charged element to identifycompounds with enhanced pharmacokinetic properties.

It is a further object of the present invention to provide apharmacophore model that is modified to identify compounds with enhancedpharmacokinetic properties.

It is a further object of the present invention to provide an accurateQSAR model associated with the pharmacophore model that can predict theactivity of any identified compound with 82% accuracy.

It is a further object of the present invention to identify compoundsthat demonstrate antibacterial activity against multidrug resistant S.pneumoniae when tested in whole cell assays.

It is yet a further object of the present invention to provide a methodof identifying antibacterial agents with enhanced pharmacokineticproperties comprising the steps of a) developing pharmacophore modelsbased on known glutamate racemase inhibitors; b) excluding models withmore than one charged element to obtain remaining models with enhancedpharmacokinetic properties; and c) identifying compounds by searchingchemical databases for compounds comprising a structure closest to theremaining models.

It is yet a further object of the present invention to provide a methodof identifying antibacterial agents with enhanced pharmacokineticproperties comprising the steps of a) developing pharmacophore modelsbased on known glutamate racemase inhibitors; b) modifying elements inthe pharmacophore models to enhance pharmacokinetic properties of themodels and obtain modified models; and c) identifying compounds bysearching chemical databases for compounds comprising a structureclosest to the modified models.

It is yet a further object of the present invention to provide apharmacophore model comprising the structure shown in FIG. 4, wherein N9represents a negative ionizable site, D7 a hydrogen bond donor site, A1a hydrogen bond acceptor site and both R11 and R12 are aromatic ringsites.

It is yet a further object of the present invention to provide a methodof treating a S. pneumoniae infection comprising administering to amammal in need of treatment, an effective amount of a compoundcomprising the structure shown in FIG. 6, wherein R comprises —CH3, —F,—Cl, or —Br.

It is yet a further object of the present invention to provide a methodof treating a S. pneumoniae infection comprising administering to amammal in need of treatment, an effective amount of4-(4-fluorophenyl)-2-{[2-(1H-indol-3-yl)ethyl]amino}-4-oxobutanoic acid,2-(2-(1H-indol-3-yl)ethylamino)-4-oxo-4-p-tolylbutanoic acid,2-(2-(1H-indol-3-yl)ethylamino)-4-(4-chlorophenyl)-4-oxobutanoic acid,2-(2-(1H-indol-3-yl)ethylamino)-4-(4-bromophenyl)-4-oxobutanoic acid, ora combination thereof.

There has thus been outlined, rather broadly, the more importantfeatures of the invention in order that the detailed description thereofthat follows may be better understood, and in order that the presentcontribution to the art may be better appreciated. There are, of course,additional features of the invention that will be described furtherhereinafter.

In this respect, before explaining at least one embodiment of theinvention in detail, it is to be understood that the invention is notlimited in its application to the details of construction and to thearrangements of the components set forth in the following description orillustrated in the drawings. The invention is capable of otherembodiments and of being practiced and carried out in various ways.Also, it is to be understood that the phraseology and terminologyemployed herein are for the purpose of description and should not beregarded as limiting.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may be readily utilized as a basisfor the designing of other structures, methods and systems for carryingout the several purposes of the present invention. It is important,therefore, that equivalent constructions insofar as they do not departfrom the spirit and scope of the present invention, are included in thepresent invention.

For a better understanding of the invention, its operating advantagesand the aims attained by its uses, reference should be made to theaccompanying drawings and descriptive matter which illustrate preferredembodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic representation of the bacterial peptidoglycanbiosynthetic pathway showing known antibiotic targets.

FIG. 2 shows the general structure of glutamate racemase inhibitors.

FIG. 3 is a schematic representation of the whole cell assay used toverify antibacterial activity against multidrug resistant S. pneumoniae.

FIG. 4 is a schematic representation of the pharmacophore model of thepresent invention.

FIG. 5 is a plot showing the correlation between experimental activityof the known glutamate racemase inhibitors and their calculated activityusing the pharmacophore model of the present invention.

FIG. 6 shows the general structure of the compound of the presentinvention.

FIG. 7 shows the chemical structure of2-(2-(1H-indol-3-yl)ethylamino)-4-oxo-4-p-tolylbutanoic acid.

FIG. 8 shows the chemical structure of2-(2-(1H-indol-3-yl)ethylamino)-4-(4-fluorophenyl)-4-oxobutanoic acid.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 is a schematic representation of the bacterial peptidoglycanbiosynthetic pathway showing known antibiotic targets. D-glutamate isrequired for the synthesis of the cell wall. The enzyme glutamateracemase (also known as MurI) is the enzyme that converts L-glutamate tothe necessary D-glutamate for bacterial cell survival.

Because there is no structure available for glutamate racemase from S.pneumoniae, ligand-based drug design approaches can be used to developpotent glutamate racemase inhibitors. Known glutamate racemaseinhibitors³ were not as effective as desired. They were highly chargedcompounds and, therefore, were expected to have poor membranepermeability. FIG. 2 shows the general structure of glutamate racemaseinhibitors. All inhibitors were derivatives of D-glutamic acid, whichexplains the highly charged nature of these inhibitors. R is analiphatic or an aromatic hydrophobic group. They showed antibacterialactivity against only S. pneumonia, which could have been due to theirpoor membrane permeability. Calculations of the absorption,distribution, metabolism and excretion (ADME) properties of theseinhibitors strongly support this hypothesis (see Table 3) especially,the oil/water partition coefficient (Po/w) values which can be used asan indicator of membrane permeability. Another possible reason for thenarrow scope of antibacterial activity could be the low similarity amongglutamate racemases from different organisms. ³ Id.

To develop potent glutamate racemase inhibitors with improved lipidsolubility and, hence, better antibacterial spectrum, the method of thepresent invention involves extracting a pharmacophore model from a groupof known glutamate racemase inhibitors and modifying it so that thefunctional groups required for glutamate racemase inhibition arepreserved while enhancing lipid solubility.

Commercially available software (Schrödinger's PHASE) was used forpharmacophore modeling and database screening. The overall protocol foridentifying new glutamate racemase inhibitors with improvedpharmacokinetic properties involves:

-   -   1. Developing a pharmacophore model for glutamate racemase        inhibitors from a group of already known inhibitors with poor        pharmacokinetic properties.    -   2. Modify the elements in the pharmacophore model to enhance the        pharmacokinetic properties of potential inhibitors.    -   3. Developing a Quantitative Structure-Activity Relationship        (QSAR) model that can predict glutamate racemase inhibition        activity for unknown compounds with reasonable accuracy.    -   4. Searching several databases of commercially available        chemical compounds with the developed pharmacophore model to        identify new potential inhibitors.    -   5. In silico calculation of pharmacokinetic properties of the        identified compounds.    -   6. Screening the identified compounds and selecting only those        with enhanced potency and pharmacokinetic properties for        antibacterial activity testing.

More specifically, the methods involve the following:

Developing the Pharmacophore Model:

Database Searching and Compound Selection:

The method of developing the pharmacophore model comprises the steps ofa) identifying known glutamate racemase inhibitors with biologicalactivity and poor pharmacokinetic properties; b) identifying elementscommon to all the known glutamate racemase inhibitors; and c) developingmodels that contain about 3-6 common elements, preferably 5 elements.According to a preferred embodiment, the biological activity comprisesantibacterial activity, more preferably, the biological activity isexperimentally determined based on at least one of IC50, Ki, MIC valueand any other experimental measures of biological activity.

The method further comprises the steps of a) developing a quantitativestructure-activity relationship (QSAR) model; b) selecting a QSAR modelwith the highest (R²) value; and c) identifying compounds by searchingchemical databases for compounds comprising a structure closest to theselected model. According to a preferred embodiment, the QSAR modelpredicts at least one of the IC₅₀, Ki, MIC value and any other measureof biological activity of the compounds with an accuracy of at leastabout 70%, preferably 80%, more preferably 90%. According to a furtherpreferred embodiment, the method further comprises the step ofcalculating the IC₅₀ value of the identified compounds.

The step of developing the QSAR model comprises the steps of a)identifying known glutamate racemase inhibitors with poorpharmacokinetic properties; b) classifying the known inhibitors intogroups depending on their biological activity; c) creating a trainingset comprising about 25 inhibitors, wherein the training set comprisesat least one known inhibitor from each group; d) creating a test setcomprising the remaining known inhibitors; e) developing the QSAR modelbased on the training set; f) using the QSAR model to calculate at leastone of the IC₅₀, Ki, MIC value and any other measure of biologicalactivity of the test set; and g) calculating the R² value by comparingthe calculated IC₅₀, Ki, MIC value and any other measure of biologicalactivity of the test set with the known IC₅₀, Ki, MIC value and anyother measure of biological activity of the test set. According to apreferred embodiment, the step of classifying the known inhibitors bytheir biological activity comprises classifying the known inhibitors ashighly active if they have an IC₅₀ value of less than 0.07, moderatelyactive if they have an IC₅₀ value of 0.07-0.8, active if they have anIC₅₀ value of 0.8-10, slightly active if they have an IC₅₀ value of10-100, and weakly active if they have an IC₅₀ of above 100.

Whole-cell Assays: Selected compounds were assayed against S. pneumoniaeon blood agar plates as shown on FIG. 3.

Table 1 shows the results of six pharmacophore models extracted from the47 known glutamate racemase inhibitors⁵. The R² value delineates howaccurate a model is in predicting an inhibitor's IC₅₀. Model 6 had thehighest R² value. ⁵ Id.

TABLE 1 Model Number R² Value 1 0.20 2 0.58 3 0.80 4 0.76 5 0.77 6 0.82

FIG. 4 is a schematic representation of Model 6 (ADNRR2584), thepharmacophore model of the present invention. The pharmacophore model,Model 6, contains five sites as shown seen in FIG. 4: site A1 (spherewith 2 arrows) represents a hydrogen bond acceptor functional group,site N9 (sphere with no arrow) represents a negative ionizablefunctional group), site D7 (sphere with 1 arrow) represents a hydrogenbond donor functional group), and both sites R11 and R12 (small rings)represent an aromatic ring. Distances and angles between the sites areshown in Tables 2 and 3, respectively. According to a preferredembodiment, only one charged center (N9) is maintained in the model. Theother two charged centers are replaced by neutral groups to enhance thelipophilicity of identified compounds, i.e., the negatively chargedelements in the model are replaced with hydrogen-bond acceptor groupsand the positively charged elements in the model are replaced withhydrogen-bond donor groups.

TABLE 2 Model 6 (ADNRR2584) inter-site distances. Site 1 Site 2 Distancein Å A1 D7 4.398 A1 N9 5.034 A1 R11 5.847 A1 R12 7.940 D7 N9 3.376 D7R11 7.186 D7 R12 9.163 N9 R11 4.436 N9 R12 6.165 R11 R12 2.136

TABLE 3 Model 6 (ADNRR2584) inter-site angles. Site 1 Site 2 Site 3Angle in degrees D7 A1 N9 41.3 D7 A1 R11 87.9 D7 A1 R12 91.3 N9 A1 R1147.4 N9 A1 R12 50.9 R11 A1 R12 3.6 A1 D7 N9 79.5 A1 D7 R11 54.4 A1 D7R12 60.0 N9 D7 R11 26.7 N9 D7 R12 22.1 R11 D7 R12 5.7 A1 N9 D7 59.2 A1N9 R11 76.0 A1 N9 R12 89.7 D7 N9 R11 133.3 D7 N9 R12 146.1 R11 N9 R1213.8 A1 R11 D7 37.7 A1 R11 N9 56.6 A1 R11 R12 166.5 D7 R11 N9 20.0 D7R11 R12 154.7 N9 R11 R12 136.6 A1 R12 D7 28.7 A1 R12 N9 39.3 A1 R12 R119.9 D7 R12 N9 11.9 D7 R12 R11 19.6 N9 R12 R11 29.6

FIG. 5 shows the correlation between experimental activity of the knownglutamate racemase inhibitors and their calculated activity using Model6. The R² plot for Model 6 shows how well the predicted IC₅₀ valuesagree with their corresponding experimental values.

Table 4 shows 17 compounds identified by Model 6 as potential glutamateracemase inhibitors. Compounds A and B had the lowest IC₅₀, i.e.,highest activity, and therefore, their ADME properties were calculatedand these compounds were selected for bacterial assays.

TABLE 4 Predicted Entry ID Title No. Sites Matched Fitness IC₅₀ mg/mL 1ligand_7567 5 1.4 6.3 2 ligand_31939 5 1.3 1.1 3 ligand_49854 5 1.2 6.44 ligand_48140 5 1.2 0.65 5 ligand_26895 5 1.1 13.8 6 ligand_48139 5 1.11.1 7 ligand_48150 5 1.1 1.8 8 ligand_39818 5 1 1.7 A ligand_48151 5 0.90.45 B ligand_48287 5 0.9 0.49 11  ligand_48136 5 0.8 1.1 12 ligand_32329 5 0.8 1.3 13  ligand_48147 5 0.8 1.7 14  ligand_26896 5 0.72.6 15  ligand_48148 5 0.5 1.2 16  ligand_48286 5 0.5 2.2 17 ligand_48137 5 0.1 1.1

Table 5 shows the relevant ADME properties as calculated by QikProp forthe known compounds⁶ and compounds A and B above. The calculated ADMEproperties are: P_(O/W) which is an indicator of the lipophilicity ofthe compound (low values represent poor lipid solubility), S which isthe aqueous solubility, and Caco-2 which is an indicator of the humangut permeability. Ranges in parentheses represent ranges for 90% ofdrugs in the market today. ⁶ Id.

TABLE 5 Log P_(O/W) Log S^(b) Caco-2 nm/sec Compound (−2.0 to 6.5) (−6.5to 0.5) (<25 poor and >500 great) Known compounds 24 0.53 −2.886 1 60−0.835 −2.128 0 69 −0.193 −2.042 1 74 0.142 −2.493 1 Compounds of thepresent invention A 2.0 −5.0 18.9 B 1.9 −4.7 18.9

For the known compounds in Table 5, the structure is as shown in FIG. 2,with the R as listed below in Table 6:

TABLE 6 Known Compound R Group 24

60

69

74

The antibacterial activity of Compound B against S. pneumoniae R6 strainwas assayed as shown in FIG. 3. Compound B was tested at three differentconcentrations, 0.5 μg/mL, 0.75 μg/mL, and 1.0 μg/mL as shown in FIG. 3and inhibition zones were compared to that around DMSO, which is thesolvent used to dissolve Compound B. Compound B showed significantantibacterial activity as compared to the DMSO (data not shown).Compound A was also tested but showed weaker antibacterial activity thanCompound B (data not shown).

FIG. 6 shows the general structure of the compound identified by Model 6(ADNRR2584), wherein R comprises —CH3, —F, —Cl, or —Br. The structure ofCompound A is shown in FIG. 7, which shows2-(2-(1H-indol-3-yl)ethylamino)-4-oxo-4-p-tolylbutanoic acid, and thestructure of Compound B is shown in FIG. 8, which shows2-(2-(1H-indol-3-yl)ethylamino)-4-(4-fluorophenyl)-4-oxobutanoic acid.The protocol for identifying new antibacterial agents using Model 6(ADNRR2584) involves searching databases of commercially availablechemical compounds with the model using the appropriate computer programto identify new potential inhibitors. The compounds2-(2-(1H-indol-3-yl)ethylamino)-4-(4-chlorophenyl)-4-oxobutanoic acidand 2-(2-(1H-indol-3-yl)ethylamino)-4-(4-bromophenyl)-4-oxobutanoic acidwere also identified in this fashion.

Through ligand-based drug design approach, a pharmacophore model thatcan identify glutamate racemase inhibitors with antibacterial activitywith 82% success rate can be identified. The present invention showsthat through modifications of pharmacophore sites, the ADME propertiesof the identified compounds can be controlled.

The present invention contemplates using Model 6 to search more andlarger chemical compound databases to identify compounds with evenbetter antibacterial activities and better membrane permeabilities. Thepresent invention also contemplates determining the antibacterialspectrum of the identified compounds by testing them against differentstrains of bacteria. The present invention further contemplates mixingtogether these results and the results from structure-based drug designapproaches to develop glutamate racemase with broader spectrum ofantibacterial activity.

Having now described a few embodiments of the invention, it should beapparent to those skilled in the art that the foregoing is merelyillustrative and not limiting, having been presented by way of exampleonly. Numerous modifications and other embodiments are within the scopeof the invention and any equivalent thereto. It can be appreciated thatvariations to the present invention would be readily apparent to thoseskilled in the art, and the present invention is intended to includethose alternatives.

Further, since numerous modifications will readily occur to thoseskilled in the art, it is not desired to limit the invention to theexact construction and operation illustrated and described, andaccordingly, all suitable modifications and equivalents may be resortedto as falling within the scope of the invention.

1. A method of treating a Streptococcus pneumoniae infection comprisingadministering to a mammal in need of treatment, an effective amount of acompound comprising the structure

wherein R comprises —CH3, —F, —Cl, and —Br.
 2. The method of claim 1,wherein the compound comprises2-(2-(1H-indol-3-yl)ethylamino)-4-(4-fluorophenyl)-4-oxobutanoic acid.3. The method of claim 1, wherein the compound comprises2-(2-(1H-indol-3-yl)ethylamino)-4-oxo-4-p-tolylbutanoic acid.
 4. Themethod of claim 1, wherein the compound comprises2-(2-(1H-indol-3-yl)ethylamino)-4-(4-chlorophenyl)-4-oxobutanoic acid.5. The method of claim 1, wherein the compound comprises2-(2-(1H-indol-3-yl)ethylamino)-4-(4-bromophenyl)-4-oxobutanoic acid.